COLT
2008
Springer
13 years 9 months ago
2008
Springer
We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
We consider the question of why modern machine learning methods like support vector machines outperform earlier nonparametric techniques like kNN. Our approach investigates the lo...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
Coordinate gradient learning is motivated by the problem of variable selection and determining variable covariation. In this paper we propose a novel unifying framework for coordi...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
Prediction from expert advice is a fundamental problem in machine learning. A major pillar of the field is the existence of learning algorithms whose average loss approaches that ...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
In the multi-armed bandit (MAB) problem there are k distributions associated with the rewards of playing each of k strategies (slot machine arms). The reward distributions are ini...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
We study on-line decision problems where the set of actions that are available to the decision algorithm vary over time. With a few notable exceptions, such problems remained larg...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
A Hilbert space embedding for probability measures has recently been proposed, with applications including dimensionality reduction, homogeneity testing and independence testing. ...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
In recent work, Kalai, Klivans, Mansour, and Servedio [KKMS05] studied a variant of the "Low-Degree (Fourier) Algorithm" for learning under the uniform probability distr...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
We study the problem of clustering discrete probability distributions with respect to the Kullback-Leibler (KL) divergence. This problem arises naturally in many applications. Our...
COLT
2008
Springer
13 years 9 months ago
2008
Springer
We study the properties of the agnostic learning framework of Haussler [Hau92] and Kearns, Schapire and Sellie [KSS94]. In particular, we address the question: is there any situat...